[915] | 1 | % $Id: fundamentals_of_les.tex 1649 2015-09-15 16:34:42Z boeske $ |
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| 2 | \input{header_tmp.tex} |
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[1526] | 3 | %\input{header_lectures.tex} |
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[915] | 4 | |
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| 5 | \usepackage[utf8]{inputenc} |
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[1526] | 6 | \usepackage{ngerman} |
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[915] | 7 | \usepackage{pgf} |
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| 8 | \usepackage{subfigure} |
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| 9 | \usepackage{units} |
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| 10 | \usepackage{multimedia} |
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| 11 | \usepackage{hyperref} |
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| 12 | \newcommand{\event}[1]{\newcommand{\eventname}{#1}} |
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| 13 | \usepackage{xmpmulti} |
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| 14 | \usepackage{tikz} |
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| 15 | \usetikzlibrary{shapes,arrows,positioning} |
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| 16 | \def\Tiny{\fontsize{4pt}{4pt}\selectfont} |
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| 17 | |
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| 18 | %---------- neue Pakete |
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| 19 | \usepackage{amsmath} |
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| 20 | \usepackage{amssymb} |
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| 21 | \usepackage{multicol} |
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[1526] | 22 | \usepackage{pdfcomment} |
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[915] | 23 | |
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[1526] | 24 | \institute{Institute of Meteorology and Climatology, Leibniz UniversitÀt Hannover} |
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| 25 | \selectlanguage{english} |
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[915] | 26 | \date{last update: \today} |
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| 27 | \event{PALM Seminar} |
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| 28 | \setbeamertemplate{navigation symbols}{} |
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| 29 | |
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| 30 | \setbeamertemplate{footline} |
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| 31 | {% |
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| 32 | \begin{beamercolorbox}[rightskip=-0.1cm]& |
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| 33 | {\includegraphics[height=0.65cm]{imuk_logo.pdf}\hfill \includegraphics[height=0.65cm]{luh_logo.pdf}} |
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| 34 | \end{beamercolorbox} |
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| 35 | \begin{beamercolorbox}[ht=2.5ex,dp=1.125ex,% |
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| 36 | leftskip=.3cm,rightskip=0.3cm plus1fil]{title in head/foot}% |
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| 37 | {\leavevmode{\usebeamerfont{author in head/foot}\insertshortauthor} \hfill \eventname \hfill \insertframenumber \; / \inserttotalframenumber}% |
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| 38 | \end{beamercolorbox}% |
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| 39 | % \begin{beamercolorbox}[colsep=1.5pt]{lower separation line foot}% |
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| 40 | % \end{beamercolorbox} |
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| 41 | }%\logo{\includegraphics[width=0.3\textwidth]{luhimuk_logo.eps}} |
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| 42 | |
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| 43 | \title[Fundamentals of Large-Eddy Simulation]{Fundamentals of Large-Eddy Simulation} |
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[1526] | 44 | \author{PALM group} |
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[915] | 45 | |
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| 46 | % Notes: |
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| 47 | % jede subsection bekommt einen punkt im menu (vertikal ausgerichtet. |
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| 48 | % jeder frame in einer subsection bekommt einen punkt (horizontal ausgerichtet) |
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| 49 | \begin{document} |
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| 50 | %Folie 1 |
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| 51 | \begin{frame} |
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| 52 | \titlepage |
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[948] | 53 | \pdfnote{maronga}{ |
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| 54 | Welcome to the PALM Tutorial!\textCR\textCR |
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| 55 | We have placed many helpful comments throughout the presentations that will hopefully ease your first steps with PALM.\textCR\textCR |
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| 56 | In case you find it hard to follow at specific points that have not been (or insufficiently) commented, please let us know! We appreciate feedback that helps improving the tutorial.\textCR\textCR |
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| 57 | Good luck! - The PALM Group at IMUK |
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| 58 | } |
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[915] | 59 | \end{frame} |
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| 60 | |
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| 61 | \section{The Role of Turbulence} |
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| 62 | \subsection{The Role of Turbulence} |
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| 63 | |
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| 64 | % Folie 2 |
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| 65 | \begin{frame} |
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| 66 | \frametitle{The Role of Turbulence (I)} |
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| 67 | \begin{itemize} |
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| 68 | \item<1->{\textbf{Most flows in nature \& technical applications are turbulent}} |
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| 69 | \item<2->{\textbf{Significance of Turbulence}} |
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| 70 | \begin{itemize} |
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| 71 | \item<2->{\underline{Meteorology / Oceanography:} Transport processes of momentum, heat, water vapor as well as other scalars} |
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| 72 | \item<2->{\underline{Health care:} Air pollution} |
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| 73 | \item<2->{\underline{Aviation, Engineering:} Wind impact on buildings, power output of windfarms} |
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| 74 | \end{itemize} |
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| 75 | \item<3->{\textbf{Characteristics of turbulence}} |
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| 76 | \begin{itemize} |
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| 77 | \item<3->{non-periodical, 3D stochastic movements} |
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| 78 | \item<3->{mixes air and its properties on scales between large-scale advection and molecular diffusion} |
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| 79 | \item<3->{non-linear $\rightarrow$ energy is distributed smoothly with wavelength} |
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| 80 | \item<3->{wide range of spatial and temporal scales} |
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| 81 | \end{itemize} |
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| 82 | \end{itemize} |
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| 83 | \end{frame} |
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| 84 | |
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| 85 | % Folie 3 |
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| 86 | \begin{frame} |
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| 87 | \frametitle{The Role of Turbulence (II)} |
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| 88 | \begin{columns}[c] |
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| 89 | \column{0.5\textwidth} |
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| 90 | \scriptsize |
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| 91 | \begin{itemize} |
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| 92 | \item<2->{\textbf{Large eddies:} $\unit[10^3]{m}$ ($L$), $\unit[1]{h}$ \\ |
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| 93 | \textbf{Small eddies:} $\unit[10^{-3}]{m}$ ($\eta$), \unit[0.1]{s}} |
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| 94 | \item<3->{\textbf{Energy production and dissipation on different scales}} |
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| 95 | \begin{itemize} |
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| 96 | \item<3->{\begin{scriptsize} Large scales: shear and buoyant production \end{scriptsize}} |
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| 97 | \item<3->{\begin{scriptsize} Small scales: viscous dissipation \end{scriptsize}} |
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| 98 | \end{itemize} |
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| 99 | \item<4->{\textbf{Large eddies contain most energy}} |
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| 100 | \item<5->{\textbf{Energy-cascade} \\ |
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| 101 | Large eddies are broken up by instabilities and their energy is handled down to smaller scales.} |
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| 102 | \end{itemize} |
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| 103 | \normalsize |
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| 104 | \column{0.5\textwidth} |
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| 105 | \onslide<3->{ |
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| 106 | \includegraphics[width=\textwidth, height=0.9\textheight]{fundamentals_of_les_figures/Role_of_Turbulence_2.png}} |
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| 107 | \end{columns} |
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| 108 | \end{frame} |
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| 109 | |
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| 110 | \section{The Reynolds Number} |
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| 111 | \subsection{The Reynolds Number} |
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| 112 | |
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| 113 | % Folie 4 |
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| 114 | \begin{frame} |
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| 115 | \frametitle{The Reynolds Number (Re)} |
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| 116 | \begin{columns}[c] |
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| 117 | \column{0.6\textwidth} |
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| 118 | \onslide<1->{ |
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| 119 | $\frac{L}{\eta} \approx Re^{3/4} \approx 10^6$ \quad \begin{small} (in the atmosphere) \end{small}} |
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| 120 | \par\bigskip |
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| 121 | \onslide<2->{ |
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| 122 | $Re = \frac{\left| \textbf{u} \cdot \nabla \textbf{u} \right|}{\left| \nu \nabla^2 \textbf{u} \right|} \hat{=} \frac{LU}{\nu} \qquad \frac{\textnormal{inertia forces}}{\textnormal{viscous forces}} $} |
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| 123 | \column{0.4\textwidth} |
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| 124 | \footnotesize |
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| 125 | \onslide<1->{ |
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| 126 | \textbf{u} 3D wind vector |
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| 127 | |
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| 128 | $\nu$ kinematic molecular viscosity |
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| 129 | |
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| 130 | $L$ outer scale of turbulence |
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| 131 | |
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| 132 | $U$ characteristic velocity scale |
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| 133 | |
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| 134 | $\eta$ inner scale of turbulence |
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| 135 | \begin{scriptsize}(Kolmogorov dissipation length) \end{scriptsize} } |
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| 136 | \end{columns} |
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| 137 | \normalsize |
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| 138 | \par\bigskip |
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| 139 | \par\bigskip |
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| 140 | \onslide<3->{ |
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| 141 | $ \Rightarrow $ \underline{Number of gridpoints for a 3D simulation:} |
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| 142 | \par\bigskip |
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| 143 | $ \left( \frac{L}{\eta} \right)^3 \approx Re^{9/4} \approx 10^{18}$ (in the atmosphere)} |
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| 144 | \end{frame} |
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| 145 | |
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| 146 | \section{Classes of Turbulence Models} |
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| 147 | \subsection{Classes of Turbulence Models} |
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| 148 | |
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| 149 | % Folie 5 |
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| 150 | \begin{frame} |
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| 151 | \frametitle{Classes of Turbulence Models (I)} |
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| 152 | \begin{itemize} |
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| 153 | \item{\textbf{Direct numerical Simulation (DNS)}} |
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| 154 | \begin{itemize} |
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| 155 | \item<2->{\textbf{Most straight-forward approach:}} |
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| 156 | \begin{itemize} |
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| 157 | \item<2->{Resolve all scales of turbulent flow explicitly.} |
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| 158 | \end{itemize} |
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| 159 | \item<3->{\textbf{Advantage:}} |
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| 160 | \begin{itemize} |
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| 161 | \item<3->{(In principle) a very accurate turbulence representation.} |
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| 162 | \end{itemize} |
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| 163 | \item<4->{\textbf{Problem:}} |
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| 164 | \begin{itemize} |
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[1649] | 165 | \item<4->{Limited computer resources (1996: $\sim$ $10^8$, today: $\sim$ $10^{12}$ gridpoints, |
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[915] | 166 | but $\sim$ $10^{18}$ gridpoints needed, see prior slide).} |
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| 167 | \item<4->{$\unit[1]{h}$ simulation of $10^9$ ($2048^3$) gridpoints on $512$ processors of the HLRN supercomputer needs $\unit[10]{h}$ CPU time.} |
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| 168 | \end{itemize} |
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| 169 | \item<5->{\textbf{Consequences:}} |
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| 170 | \begin{itemize} |
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| 171 | \item<5->{DNS is restricted to moderately turbulent flows (low Reynolds-number flows).} |
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| 172 | \item<5->{Highly turbulent atmospheric turbulent flows cannot be simulated.} |
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| 173 | \end{itemize} |
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| 174 | \end{itemize} |
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| 175 | \end{itemize} |
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| 176 | \end{frame} |
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| 177 | |
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| 178 | % Folie 6 |
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| 179 | \begin{frame} |
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| 180 | \frametitle{Classes of Turbulence Models (II)} |
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| 181 | \begin{itemize} |
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| 182 | \item{\textbf{Reynolds averaged (Navier-Stokes) simulation (RANS)}} |
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| 183 | \begin{itemize} |
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| 184 | \item<2->{\textbf{Opposite strategy:}} |
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| 185 | \begin{itemize} |
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| 186 | \item<2->{Applications that only require average statistics of the flow (i.e. the mean flow).} |
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| 187 | \item<2->{Integrate merely the ensemble-averaged equations.} |
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| 188 | \item<2->{Parameterize turbulence over the whole eddy spectrum.} |
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| 189 | \end{itemize} |
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| 190 | \item<3->{\textbf{Advantage:}} |
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| 191 | \begin{itemize} |
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| 192 | \item<3->{Computationally inexpensive, fast.} |
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| 193 | \end{itemize} |
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| 194 | \item<4->{\textbf{Problem:}} |
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| 195 | \begin{itemize} |
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| 196 | \item<4->{Turbulent fluctuations not explicitly captured.} |
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| 197 | \item<4->{Parameterizations are very sensitive to large-eddy structure that depends on |
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| 198 | environmental conditions such as geometry and stratification $\rightarrow$ |
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| 199 | Parameterizations are not valid for a wide range of different flows.} |
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| 200 | \end{itemize} |
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| 201 | \item<5->{\textbf{Consequence:}} |
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| 202 | \begin{itemize} |
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| 203 | \item<5->{Not suitable for detailed turbulence studies.} |
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| 204 | \end{itemize} |
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| 205 | \end{itemize} |
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| 206 | \end{itemize} |
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| 207 | \end{frame} |
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| 208 | |
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| 209 | % Folie 7 |
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| 210 | \begin{frame} |
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| 211 | \frametitle{Classes of Turbulence Models (III)} |
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| 212 | \begin{itemize} |
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| 213 | \item{\textbf{Large eddy simulation (LES)}} |
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| 214 | \begin{itemize} |
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| 215 | \item<2->{Seeks to combine advantages and avoid disadvantages of DNS and RANS by \underline{treating |
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| 216 | large scales and small scales separately}, based on Kolmogorov's (1941) similarity theory of turbulence.} |
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| 217 | \item<3->{Large eddies are explicitly resolved.} |
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| 218 | \item<4->{The impact of small eddies on the large-scale flow is parameterized.} |
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| 219 | \item<5->{Advantages:} |
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| 220 | \begin{itemize} |
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| 221 | \item<5->{Highly turbulent flows can be simulated.} |
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| 222 | \item<5->{Local homogeneity and isotropy at large \textit{Re} (Kolmogorov's $1^\mathrm{st}$ hypothesis) leaves |
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| 223 | parameterizations uniformly valid for a wide range of different flows.} |
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| 224 | \end{itemize} |
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| 225 | \end{itemize} |
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| 226 | \end{itemize} |
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| 227 | \end{frame} |
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| 228 | |
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| 229 | \section{Concept of LES} |
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| 230 | \subsection{Concept of LES} |
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| 231 | |
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| 232 | % Folie 8 |
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| 233 | \begin{frame} |
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| 234 | \frametitle{Concept of Large Eddy Simulation (I)} |
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| 235 | \begin{columns} |
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| 236 | \column{0.55\textwidth} |
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| 237 | \begin{itemize} |
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| 238 | \item<1->{\textbf{Filtering}} |
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| 239 | \begin{footnotesize} |
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| 240 | \begin{itemize} |
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| 241 | \item<2->{Spectral cut at wavelength $\Delta x$.} |
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| 242 | \item<3->{Structures larger than $\Delta x$ are explicitly calculated (resolved scales).} |
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| 243 | \item<4->{Structures smaller than $\Delta x$ must be filtered out (subgrid scales), formally known as low-pass filtering.} |
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| 244 | \item<5->{Like for Reynolds averaging: split variables in mean part and fluctuation, spatially average the model equations, e.g.:} |
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| 245 | \end{itemize} |
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| 246 | \end{footnotesize} |
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| 247 | \onslide<6->{\begin{center} $w = \overline{w} + w', \theta = \overline{\theta} + \theta'$ \end{center}} |
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| 248 | \end{itemize} |
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| 249 | \column{0.45\textwidth} |
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| 250 | \includegraphics[width=\textwidth]{fundamentals_of_les_figures/Concept_of_LES.png} |
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| 251 | \end{columns} |
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| 252 | \end{frame} |
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| 253 | |
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| 254 | % Folie 9 |
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| 255 | \begin{frame} |
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| 256 | \frametitle{Concept of Large Eddy Simulation (II)} |
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| 257 | \begin{itemize} |
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| 258 | \item<1->{\textbf{Parameterization}} |
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| 259 | \begin{footnotesize} |
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| 260 | \begin{itemize} |
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| 261 | \item<2->{The filter procedure removes the small scales from the model equations, but it produces new unknowns, mainly averages of fluctuation products.} |
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| 262 | \begin{itemize} |
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| 263 | \item<2->{eg. $\overline{w'\theta'}$} |
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| 264 | \end{itemize} |
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| 265 | \item<3->{These unknowns describe the effect of the unresolved, small scales on the resolved, large scales; therefore it is important to include them in the model.} |
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| 266 | \item<4->{We do not have information about the variables (e.g., vertical wind component and potential temperature) on these small scales of their fluctuations.} |
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| 267 | \item<5->{Therefore, these unknowns have to be parameterized using information from the resolved scales.} |
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| 268 | \begin{itemize} |
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| 269 | \item<5->{A typical example is the flux-gradient relationship, e.g.,} |
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| 270 | \end{itemize} |
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| 271 | \end{itemize} |
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| 272 | \end{footnotesize} |
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| 273 | \end{itemize} |
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| 274 | \onslide<5->{ |
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| 275 | \begin{center} |
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| 276 | $ \overline{w'\theta'} = - \nu_\mathrm{h} \cdot \frac{\partial \overline{\theta}}{\partial z} $ |
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| 277 | \end{center}} |
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| 278 | \end{frame} |
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| 279 | |
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| 280 | \end{document} |
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